About egm-review-loop
egm-review-loop is a skill that coordinates iterative, multi-agent reviews of a target document. It combines fresh-context auditors with a persistent resolver that evaluates findings and applies approved edits.
Key features
- 01Re-scans target ranges each round
- 02Dispatches specialized reviewers
- 03Combines and categorizes findings
- 04Supports approved document repairs
- 05Waits for user confirmation between rounds
Use cases
- 01Reviewing a changing design document
- 02Running repeated audits against standards
- 03Applying selected reviewer fixes
- 04Pausing a review for user decisions
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ google/ elephant-goldfish-model --skill egm-review-loopAfter installing, type/egm-review-loopin Claude Code to confirm it loaded.
Bundled filestest_scenarios.yamlTEST.md
Details
From the project READMEGoldfish Review: Loop (Orchestration Driver)
When running in Codex or ChatGPT Work, first read Codex integration.
In Claude Code or Cowork, read ${CLAUDE_PLUGIN_ROOT}/docs/claude.md first.
Overview
This skill acts as the central orchestration engine driving the multi-agent review loop. It coordinates two distinct agent memory models:
- The Goldfish (Adversarial Auditors): Subagents spawned in isolated, fresh context windows to catch unstated assumptions without historical bias.
- The Elephant (Persistent Resolver): The primary agent context holding institutional knowledge to evaluate findings and apply approved repairs.
The driver manages argument intake, resolves paths for reviewers and standards, unconditionally re-parses target line ranges before every iteration, spawns concurrent specialized Goldfish auditors based on configuration, and coordinates with the Elephant context to resolve findings.
Delegation
A Goldfish runs in a fresh context with no conversation history. Spawn each
subagent with your harness's subagent tool (Antigravity: invoke_subagent; Claude Code: Agent; Codex: spawn_agent). Each subagent is defined in agents/<file>.md, and its
frontmatter name (for example egm-zoom-out) is the subagent type to request
where your harness registers named subagents. Otherwise spawn a general-purpose
subagent and tell it to read that persona file first. Pass the prompt verbatim
and wait for the report. If your harness cannot nest subagents,
use direct dispatch instead of the synthesizer. See docs/harnesses.md.
If your harness has no subagent tool, stop and tell the user: a review in the same
context is not a Goldfish review.
Inputs
The caller or user provides exactly these parameters:
TargetFile: Absolute or relative path to target document.SemanticTarget: Descriptive targeting string (e.g., "Target the H4 block with SS-ID 'S1.12'"), orfull file.Reviewers: List of reviewer names (shortnames or paths).Standards: Mapping of reviewer names to standard names (shortnames or paths).GoldfishContext: A reading list (source files, directories, or documentation URLs) fed to reviewers to establish their baseline.
Path & Standard Resolution Logic
When resolving names in Reviewers and Standards:
- Reviewer Shortnames: Map reviewer shortname (e.g.,
design_critic,structural,style,implementation_readiness,codebase_details,comprehension,zoom_out) toagents/{name}.md. The persona file defines the reviewer's core mandates, audit vectors, and output format. - Standard Shortnames: Map standard shortname (e.g.,
feature-spec-standard,implementation-readiness-standard,zoom-out-standard,heilmeier-standard,re-implementation-standard) toresources/document_standards/{name}.md. - Custom Paths: If the name contains a slash (
/), treat it as an absolute or workspace-relative path and read it directly.
Execution Workflow
Step 1: Intake & Configuration UX
Evaluate the provided inputs (TargetFile, SemanticTarget, Reviewers,
Standards, GoldfishContext).
- Identify Missing Inputs: Determine which of the required parameters are missing.
- Interactive Onboarding:
- If all inputs are present, proceed to Step 2.
- If some or all inputs are missing, interactively prompt the user only for the missing inputs, one at a time via chat messages.
- Reviewer Recommendations:
- Feature Specs: Recommend
design_critic(mapped toresources/document_standards/feature-spec-standard.md) andstructural(mapped toresources/document_standards/feature-spec-standard.md). - Implementation Plans: Recommend
implementation_readiness(mapped toresources/document_standards/implementation-readiness-standard.md) andcodebase_details.
- Feature Specs: Recommend
- Confirm Configuration: Display the consolidated plan (Target, Reviewers, and mapped Standards) and ask the user to confirm before proceeding.
Step 2: The Sharpening Loop (Iterative Cycle)
Execute the following sequence in a continuous loop:
2.1 Unconditional Target Resolution
Before every iteration, unconditionally re-scan TargetFile by reading it
and using the stable SemanticTarget string (e.g., locating the target header) to
dynamically determine the updated absolute start and end line numbers. This
ensures absolute accuracy even if the file was edited in prior rounds. (If full file mode is specified, confirm full-file line bounds).
2.2 Review Swarm Execution
- Launch Subagent Swarm:
Spawn subagents to execute the review:
- Hierarchical Dispatch (Synthesizer): Spawn the intermediate
synthesizer subagent (
agents/synthesizer.md/egm-synthesizer). The synthesizer spawns the Goldfish review swarm in parallel, deduplicates findings, writes the report artifact, and returns a single summary message to avoid context pollution in the root conversation. - Direct Dispatch (Flat Swarm): Alternatively, spawn each requested
reviewer subagent in
Reviewersdirectly. Instruct each subagent to first read its persona definition inagents/{name}.md, then auditTargetFileat the resolved line range against its designated standard inresources/document_standards/, supplyingGoldfishContext. - Each reviewer produces findings with severity (🔴 Blocker, 🟡 Major, 🟢 Nit), line numbers, discrepancy descriptions, and rationales.
- Hierarchical Dispatch (Synthesizer): Spawn the intermediate
synthesizer subagent (
- Consolidate Findings: Collect all findings across reviewers into a single
flat
FindingsList.
2.3 Aggregated Resolution Hand-off
- Pass
TargetFile, the active line range, and the aggregatedFindingsListto theegm-resolveworkflow. - Execute the resolution workflow in the primary Elephant context:
- Categorize findings into
CONTESTvs.PROPOSE FIX. - Save
goldfish_review_report.mdwith your file-writing tool. - Present the interactive decision gate (Auto accept, Continue, Interactive breakdown).
- Apply approved text repairs to
TargetFileusing your file-editing tool.
- Categorize findings into
2.4 Iteration Check & Turn Boundary
The cycle repeats until reviewers report zero remaining findings or the user explicitly halts it.
Crucial Turn-Taking Requirement: After the resolution phase finishes for a
given round, the loop driver MUST respect the turn-taking checkpoint in
egm-resolve. The driver must remain idle across human turns,
only looping back to Step 2.1 when the user explicitly confirms they wish to run
another round of review.
Step 3: Output Boundary & Final Checkpoint
Upon successful completion (e.g., zero findings remaining or manual halt):
- Programmatic Callers: If running as a subflow of
egm-review, exit cleanly to hand execution back to the parent workflow. - Manual Invocations: Output a summary of completion in chat: "The review loop has completed with zero remaining issues. Would you like to proceed to the next stage, or do you have any final questions?"